{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "threatened-orbit",
   "metadata": {},
   "source": [
    "# Air Passengers Dataset\n",
    "\n",
    "In this notebook we will prepare and store the air passengers dataset found [here](https://github.com/facebook/prophet/blob/main/examples/example_air_passengers.csv).\n",
    "\n",
    "**Citation:**\n",
    "\n",
    "Box, G. E. P., Jenkins, G. M. and Reinsel, G. C. (1976) Time Series Analysis, Forecasting and Control. Third Edition. Holden-Day. Series G.\n",
    "\n",
    "**Description of data:**\n",
    "\n",
    "The data is a monthly time series measuring the number of international airline passengers, in thousands, from 1949 to 1960."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5045cf1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1949-01-01</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1949-02-01</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1949-03-01</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1949-04-01</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1949-05-01</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ds    y\n",
       "0  1949-01-01  112\n",
       "1  1949-02-01  118\n",
       "2  1949-03-01  132\n",
       "3  1949-04-01  129\n",
       "4  1949-05-01  121"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "url = \"https://raw.githubusercontent.com/facebook/prophet/main/examples/example_air_passengers.csv\"\n",
    "df = pd.read_csv(url)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "straight-mouth",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2d0398ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Insert missing data into dataframe\n",
    "df.loc[10:11, \"y\"] = np.NaN\n",
    "df.loc[25:28, \"y\"] = np.NaN\n",
    "df.loc[40:45, \"y\"] = np.NaN\n",
    "df.loc[70:94, \"y\"] = np.NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cc2d712c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1949-11-01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds   y\n",
       "10  1949-11-01 NaN"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[10:11]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b2e9a6b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e8d075be",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"air_passengers.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd687f8a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsml",
   "language": "python",
   "name": "fsml"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
